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Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty

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  • Frank Youhua Chen

    () (Department of System Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

  • Candace Arai Yano

    () (Haas School of Business and Industrial Engineering and Operations Research Department, University of California, Berkeley, Berkeley, California 94720)

Abstract

We consider a manufacturer-retailer supply chain for a seasonal product whose demand is weather sensitive. The retailer orders from the manufacturer (supplier) prior to the selling season and then sells to the market. We examine how a manufacturer can structure a weather-linked rebate to improve his expected profit. The proposed class of rebate contracts offers several advantages over many other contract structures, including no required verification of leftover inventory and/or markdown amounts, and no adverse effect on sales effort by the retailer. We provide a thorough analysis of the manufacturer's and retailer's decisions in this context. We show that the weather-linked rebate can take many different forms, and this flexibility allows the supplier to design contracts that are Pareto improving and/or limit his risk in offering the contract and the retailer's risk in accepting it. For weather rebates with certain characteristics, the manufacturer can fully hedge his risks of offering a weather rebate by paying a risk premium; we show how this can be accomplished. We also show that the basic structural results extend to settings in which the two parties would like to limit their risk.

Suggested Citation

  • Frank Youhua Chen & Candace Arai Yano, 2010. "Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty," Management Science, INFORMS, vol. 56(8), pages 1380-1397, August.
  • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:8:p:1380-1397
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    File URL: http://dx.doi.org/10.1287/mnsc.1100.1194
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    References listed on IDEAS

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    2. Nasr, Walid W. & Maddah, Bacel, 2015. "Continuous (s, S) policy with MMPP correlated demand," European Journal of Operational Research, Elsevier, vol. 246(3), pages 874-885.
    3. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    4. Mizgier, Kamil J. & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Disentangling diversification in supply chain networks," International Journal of Production Economics, Elsevier, vol. 162(C), pages 115-124.
    5. Caliskan Demirag, Ozgun, 2013. "Performance of weather-conditional rebates under different risk preferences," Omega, Elsevier, vol. 41(6), pages 1053-1067.
    6. repec:spr:annopr:v:240:y:2016:i:2:d:10.1007_s10479-015-1948-8 is not listed on IDEAS
    7. Bertrand, Jean-Louis & Brusset, Xavier & Fortin, Maxime, 2015. "Assessing and hedging the cost of unseasonal weather: Case of the apparel sector," European Journal of Operational Research, Elsevier, vol. 244(1), pages 261-276.
    8. Haiyan Yi & Yangzhen Li, 2013. "Risk management of agricultural supply chain in China with weather compensatory contract," E3 Journal of Business Management and Economics., E3 Journals, vol. 4(7), pages 166-172.
    9. Elias, R.S. & Wahab, M.I.M. & Fang, L., 2014. "A comparison of regime-switching temperature modeling approaches for applications in weather derivatives," European Journal of Operational Research, Elsevier, vol. 232(3), pages 549-560.
    10. repec:spr:annopr:v:237:y:2016:i:1:d:10.1007_s10479-013-1453-x is not listed on IDEAS
    11. repec:eee:proeco:v:193:y:2017:i:c:p:663-676 is not listed on IDEAS
    12. repec:spr:annopr:v:240:y:2016:i:2:d:10.1007_s10479-013-1386-4 is not listed on IDEAS

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